The present invention relates generally to a temperature-aware task scheduling method for one or more graphical processing units (GPUs), and more particularly, but not by way of limitation, to a system, method, and recording medium for scheduling a task for a GPU based on a temperature and an intensiveness of each of an arithmetic logic unit (ALU) and a dynamic random-access memory (DRAM) component.
Rapid evolution of GPUs in performance, architecture, and programmability provides general and scientific computational potential far beyond their primary purpose of Graphical processing. Graphical Processing Units (GPUs) are pervasive in cognitive applications, for example. GPUs are readily available for cloud computing. For GPU users (e.g., single workload), performance is key and on which most of the conventional techniques focus improvements. For GPU owners, resource utilization is key based on how to compact more workloads into limited resources.
Conventional techniques have only considered monitoring a total temperature of the GPU when for example such total temperature is driven by an arithmetic logic unit (ALU) component, which is heavily loaded and overheated, while at the same time a DRAM unit component is not heavily loaded. Alternatively, the total temperature can be driven by a DRAM unit that is heavily loaded, and may become overheated, while an ALU unit is not loaded heavily.
There is a need in the art to consider a temperature difference of ALU and DRAM inside a GPU unit such that the ALU and DRAM can be overheated with a new task.